Transform your district heating network with our powerful Digital Twin

Start saving energy and
reduce emissions with Gradyent

Heating networks become more complex

There is an increased pressure on both cost efficiency and emission reduction. Therefore, heating networks are trying to reduce temperatures while adding more sustainable heat sources. This results in highly complex heating networks.

Current Situation

  • Few central heat sources
  • Higher temperatures
  • Lower efficiency

Vision of modern networks

  • Multiple decentral heat sources
  • Low temperatures
  • High efficiency

In the meantime, many district energy networks have old or even outdated control systems due to legacy in hard & software with limited or no dynamic optimization.

Current Control Systems

  • Legacy software, often built in-house
  • Limited insights into drivers of network efficiency
  • Stability only, no optimization

Modern Control Systems

  • Complex and dynamic modeling, made easy
  • Continuous visibility and transparency
  • AI powered intelligence
  • Automated dynamic optimization and controls

The power of the Gradyent Digital Twin

The Gradyent Digital Twin is specially designed for heating networks. In this case, a digital twin is a virtual simulation of a physical heating network. This allows for multiple simulation scenarios and analytics and therefore results in the most optimal settings for the network, any time all the time.

Digital Twin

The Gradyent platform analyses the customer heat demand on a granular basis and combines this information with the hydraulic and thermo-dynamic losses within the network. This is the optimal input for different heat sources within the network. The Gradyent Digital Twin matches customer demand and heat production in the most optimized way, resulting in lower energy losses and emission reductions!

Smart physical models

  • Combines both hydraulic and thermodynamic models
  • Defines time lags and heat propagation
  • Fills in the blanks with AI, based on available sensor data

Maximum value
from all data

  • Utilizes a holistic approach from heat sources to end customers and everything in between
  • Emphasizes combining different data sources, sensors, smart meters, and more
  • Creates a valuable Digital Twin based on a limited set of data

Fill the blanks with AI

  • Optimizes your network with Artificial Intelligence
  • Employs rapid setup as AI learns from your historic network data
  • Dynamically forecasts and optimizes in real-time
  • Automatically adapts as your network expands over time

Secure & flexible

  • No system replacement necessary
  • Always updated
  • Secure access from anywhere
  • Calculation power used to support our Digital Twin

Results in:

  • 30% lower heat losses
  • 10% lower CO2 emissions
  • 20% lower capex

Setup in less than 2 months

Our customers

Used by some of the largest District Heating networks in Europe

Automate. Gain.

Transform your heating network with the power of the Gradyent Digital Twin

  • Simulate, analyze and automate controls
  • Allow a holistic approach from heat sources to end customers and everything in between
  • Optimize temperature, hydraulics, dispatch & peaks
  • Intuitive interface to really understand your network
  • Easy setup in less than 2 months


Our platform creates value for the following application areas.


Reduce heat losses, enable low temp heat sources


Reduce pump costs & resolve pressure issues


Best possible deployment of heat sources & buffers

Smart Meters

Put smart meter data to work

Demand response

Benefit from network storage, optimize demand


A common issue for District Heating networks is that heat losses are too high. This is driven by too high temperatures in the system. Additionally, we often see that it is difficult to oversee the critical constraint of the network. By simulating the grid and advanced granular demand forecasts, new insights (e.g. forward temperatures) can be found while typical constraints (e.g. minimal temperature at consumers) are always met.


In some cases, the hydraulics of the system are considered a given. Although sometimes unpredictable, pressure issues at lower temperatures occur, or unreliable pump operation results in trips. Using our holistic and dynamic modelling approach, new opportunities arise by improving both pressure and flows, leading to energy savings.


To support multiple heat sources (e.g. Geothermal) in the network and operating on lower temperatures implies questions about which heat source needs to be utilized first, second, etc. (the so-called merit order). What will become the ‘stand-still’ points then? And how does that function in times of high electricity pricing? These are complex matters but with great emissions and financial gains.

Smart Meters

Driven by EU regulations, most of the District Heating operators have plans to invest or are already investing in smart meters. Most of the asset owners see these investments as high, mandatory, and only useful for improved invoicing processes. We also see the opportunity of using the data to granularly train the Digital Twin to an even higher extend (without compromising GDPR regulations, of course).

Demand response

Peaks in the network are important drivers for the network design and therefore the costs. Currently, some operators are making complex agreements with large customers for peak shifting. With our dynamic and holistic grid approach, we can capitalize on the potential network storage to some extent without the complex agreements.


Flexible solutions to utilize our platform based on your needs

Simulate & Improve

A Digital Twin from your network based on historical data, identifies issues and spots optimization opportunities.

Connect & Gain

A live read connection from your network into our Digital Twin allows you to live spot opportunities as a decision support system.

Automate Control

Connected to our platform, we will provide the most optimal settings to your SCADA system, any time, all the time.

Design & Expand

New or expansion plans simulate the future with our Digital Twin and allow you to validate scenarios in the most realistic way.

Our Mission – making sustainable impact on heating networks

Approximately 50% of all energy consumption in the world is used for heating and cooling. District heating networks are a large portion of this. At Gradyent, we have the ambition to assist District Heating companies in applying new technologies as our Digital Twin to strongly reduce energy consumption. For our planet, more than 10% reduction of heat losses, results in the following.

More than 2.5 billion Megaton CO2 emissions prevented annually

More than 1 billion m³ natural gas saved annually

Sector profitability up by more than 3B€ with many networks co-owned by the public

45-70 PJ (petajoule) lower heat losses

Media & Awards

Do you want to make an impact on your network?

Start saving energy and reduce emissions.


Hervé Huisman

CEO & Founder

  • Serial entrepreneur, former director at ASML and manager at McKinsey.
  • Led large operational-, IT- and strategy programs at energy and tech companies
  • Passionate about making real sustainable impact in the world


Robert Vrancken

CTO & Founder

  • Serial entrepreneur, previously Principal at Boston Consulting and CTO tech startup
  • Experienced in tech, digital analytics and AI in energy
  • PhD on fluid dynamics
  • Passionate about scaling new technologies


Niclas Kuipers


  • Experienced director for several AI and tech start- and scale-ups.
  • Prior, experience with multiple transformation programs at energy and tech companies
  • Passionate about developing sustainable business with impact


Peter Hulshof


  • Was principal at Boston Consulting Group and developer at Ortec
  • Lead large scale change and execution projects in tech and energy sectors
  • PhD in Applied Math


Freek Smelt

Director Business Development

  • Serial entrepreneur, former Business development lead at Essent
  • Owns and runs several ventures in clean energy & sustainability
  • Passionate about building great teams


Ivo Fugers

AI Lead | Data Scientist

  • Prior Senior Data scientist at ORTEC, one of the world’s leaders in optimization software and analytics solutions


Kiana Afzali

Consultant and Solutions Engineer

  • MSc of “Complex Systems Engineering and Management”
  • Experienced in analysis of complex energy infrastructures
  • Passionate about finding smart solutions for energy transition


Joost Stam

AI Engineer

  • Background in Applied Physics and Applied Mathematics, specializing in optimization and data science
  • Experience in sustainable supply-chain optimization and smart energy systems
  • Passionate about the energy transition and making real impact quickly


Sebastian Schirber

Solutions Lead

  • Previously Principal at Oliver Wyman advising on Analytics, Finance & Risk
  • PhD in climate sciences and university degree in Atmospheric Sciences / Meteorology
  • At Gradyent, combines his expertise in Analytics & Advisory with his passion for climate


Want to join our team?

Have a look at the open vacancies via the arrow below.

Get in touch

We would like to hear from you. Here is how you can reach us.

Stationsplein 45, Unit D2.112, 3013 AK Rotterdam

+31 10 3070 301